Autonomic Mul,- Agents Security System for mul,- layered distributed architectures. Chris,an Contreras

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1 Autonomic Mul,- s Security System for mul,- layered distributed architectures Chris,an Contreras

2 Agenda Introduc,on Mul,- layered distributed architecture Autonomic compu,ng system Mul,- System (MAS) Autonomic Mul, Security System JADE Framework Proposed solu,on features Conclusions Comments and ques,ons

3 Introduc,on Mul,- layered and distributed system architecture Characteris,cs : heterogeneity and complexity. Increase Cyber threats. à Security concerns grows. Maintain the SLO or SLA. We need security systems with a new approach. System that can response to current threats and future threats in a quicker and efficient way. Autonomic Compu,ng System (ACS) + Mul,- agent System(MAS) Autonomous system Self adap,ve Self protec,ng Knowledge Base à learning process

4 Mul,- layered distributed architecture

5 Architecture comparison Autonomic Compu,ng Proper,es Self- Configuring Self- Op,mizing Self- Healing Self- protec,ng MAPE- K Framework Define behavior Mul,- System Proper,es Autonomy Reac,vity Pro- ac,veness Social ability Desire Belief Inten,on (BDI) Model Define agent behavior

6 Autonomic Compu,ng Systems : MAPE- K framework Sensor Effector

7 Autonomic Compu,ng Systems : MAPE- K framework Monitor and collects the details from the managed resources using sensors. Analysis perform complex data analysis. It uses the stored knowledge data. Plan structures the ac,ons needed to achieve goals and objec,ves. Execute changes the behavior of the managed resource using effectors. Knowledge standard data shared that includes data such as topology informa,on, historical logs, metrics, symptoms and policies.

8 Autonomic Compu,ng System : Basic Proper,es

9 Mul, System proper,es Autonomy is the freedom that an agent has to make decisions. Reac;vity is the response to changes in the environment. Pro- ac;veness is the exhibi,ons of a goal- directed behavior. Social ability is the ability to successfully interact and cooperate with others agents.

10 BDI behavior model agents Desires (Goals) Beliefs (Knowledge Base) Sensor Input Interpreter (Reasoner) Event Queue Environment Plan Library (Procedural Knowledge) Inten,ons (Plan Instance) Inten,on Queue Ac;on Output

11 Mul, System Architecture Analysis Analysis Analysis Analysis Security Monitor Monitor 1 Monitor 1 1 Sensor Input Planning Planning Planning Manager Monitor Monitor 2 2 Environment Learning Learning Execu,oner Execu,oner Execu,oner Ac;on Output

12 Mul, System Architecture: Type of agents Reac,ve agent It reacts to an event and does not perform any kind of deduc,on. It always behaves in the same way. (pre- defined) Prac,cal reasoning agent It has a proac,ve behavior and make decisions on its own. First it deliberates what state of affairs to achieve Second it decides how to achieve the desired state of affairs. Predefined sets of ac,ons. (Plans) Deduc,ve reasoning agent There is a descrip,on of the environment. There are a set of rules. The agent deduces the appropriate set of ac,ons

13 Autonomic Mul,- Security System Desires (Goals) Plan Library (Procedural Knowledge) AMS DF Security Inten,ons (Plan Instance) Beliefs (Knowledge Base) Event Queue Sensor Effector Inten,on Queue

14 Autonomic Mul,- Security System JAVA DEvelopment (JADE) Framework

15 Autonomic Mul,- Security System JAVA DEvelopment (JADE) Framework

16 JADE Architecture Container: a running instance of the JADE run,me and may contain several agents (zero or more agents). PlaJorm: the set of all ac,ve containers Main container: First container to start in a pla]orm Must always be ac,ve All other containers (normal, non- main) must register with host and port of the main container. Special agents Management System (AMS). Provides the naming service Represents the authority Directory Facilitator (DF). Provides a Yellow Pages service Communica,on is based on an asynchronous message passing paradigm (ACL language).

17 Autonomic Mul,- Security System Containers External Knowledge Base Knowledge Base AMS Knowledge Base DF Main Container

18 Autonomic Mul,- Security System Cloud Mul,- layer Middleware Cross layer security Resources

19 Autonomic Mul,- Security System Mul,- layered distributed system. Cross Layer security. Mul, agents behave emula,ng the MAPE- K framework. Modeling the Security Knowledge Base with ontologies. Security policies, rules, threat signatures, etc. Supervised and unsupervised learning techniques to acquire new knowledge. s are light- weight process. Detect and react faster.

20 Autonomic Mul,- Security System JAVA DEvelopment (JADE) Framework. A fully distributed system inhabited by agents, each running as a separate thread, poten,ally on different remote machines, and capable of transparently communica,ng with one another. Full compliance with the FIPA specifica,ons. (Founda,on for Intelligent Physical s) Uses FIPA Communica,on Language (ACL). Efficient transport of asynchronous messages via a loca,on- transparent API. Support agent mobility. Support ontologies and content languages

21 Autonomic Mul,- Security System Self- Protec,ng à Secure Informa,on and Resources Predic,on Supervised and unsupervised techniques. Detec,on and Inform Monitor performance system metric, request analysis, log analysis, system corrup,on, data corrup,on, IDS. Build security traps. Iden,fy Aaack signatures, system vulnerabili,es, boalenecks, conges,on. Protec,on Change cryptographic system, communica,on protocols, ACM, flow control, etc., filter requests, drop requests, limit resource usage, limit resource access, block resources, etc.

22 Autonomic Mul,- Security System Agency trust model Security policies. Registra,on service Supervise behavior Upgrade process s autonomic security schema Self- protec,ng Self- healing Self- configuring Self- op,miza,on

23 Conclusion Autonomic Mul,- Security System for mul,- layered distributed architectures is a defense in depth approach. Autonomic Security System that can self- protec,ng, self- healing, self- configuring, self- op,miza,on itself. Knowledge base using ontologies can provide Adaptability for future threats. Reach and share knowledge across the web. JADE framework provides a solid pla]orm with poten,al grow. à Jena Apache Ontology API. s are light- weight processes that can accomplish scalability and portability. Provide support to maintain the SLA or SLO.

24 Comments and Ques,ons

Jade: Java Agent DEvelopment Framework Overview

Jade: Java Agent DEvelopment Framework Overview Stefano Mariani s.mariani@unibo.it Dipartimento di Informatica Scienza e Ingegneria (DISI) Alma Mater Studiorum Università di Bologna a Cesena Academic Year